Automated Computational Pathology to Assess Degenerative Disc Histology
Herein, we developed the first computational pathology model to phenotype disc degeneration tissue. Our model significantly correlates with traditional histopathology scoring methods, detects subtle differences between groups by directly measuring pathologic features in the images, and increases efficiency by automating the majority of the process.
Authors
- Fei San Lee
- Evie C. Barnett (ORCID: https://orcid.org/0000-0002-0483-2977)
- Richard D. Bell (ORCID: https://orcid.org/0000-0003-1562-3879)
- David J. Lillyman (ORCID: https://orcid.org/0000-0002-2470-5473)
- Rebecca A. Wachs (ORCID: https://orcid.org/0000-0001-5735-6284)
Institutions
- University of Nebraska–Lincoln (US)
- Hospital for Special Surgery (US)
- Cornell University (US)
- Arizona State University (US)
Publication Details
- Journal
- JOR Spine
- Published
- 2025-10-01
- DOI
- https://doi.org/10.1002/jsp2.70119
- Primary Topic
- Spine and Intervertebral Disc Pathology
- Type
- article
- Field-Weighted Citation Impact
- 0.00